Related references
Note: Only part of the references are listed.Deep learning assisted non-contact defect identification method using diffraction phase microscopy
Subrahmanya Keremane Narayan et al.
APPLIED OPTICS (2023)
A Robust Deep Learning-Based Damage Identification Approach for SHM Considering Missing Data
Fan Deng et al.
APPLIED SCIENCES-BASEL (2023)
Numerical Verification of the Drive-By Monitoring Method for Identifying Vehicle and Bridge Mechanical Parameters
Kyosuke Yamamoto et al.
APPLIED SCIENCES-BASEL (2023)
Application of Vehicle-Based Indirect Structural Health Monitoring Method to Railway Bridges—Simulation and In Situ Test
Michael Reiterer et al.
Applied Sciences-Basel (2023)
Atmospheric visibility prediction by using the DBN deep learning model and principal component analysis
Yufeng Wang et al.
APPLIED OPTICS (2022)
Experimental and numerical investigation of an existing railway bridge during train crossing
Michael Reiterer
BAUTECHNIK (2020)
Structural damage detection and localization using a hybrid method and artificial intelligence techniques
Azadeh Noori Hoshyar et al.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2020)
A Data-Driven Damage Identification Framework Based on Transmissibility Function Datasets and One-Dimensional Convolutional Neural Networks: Verification on a Structural Health Monitoring Benchmark Structure
Tongwei Liu et al.
SENSORS (2020)
Mitigating effects of temperature variations through probabilistic-based machine learning for vibration-based bridge scour detection
Wei Zheng et al.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING (2020)
Damage identification using deep learning and long-gauge fiber Bragg grating sensors
Wenda Zhang et al.
APPLIED OPTICS (2020)
Method of damage location determination based on a neural network using a single fiber Bragg grating sensor
Bangtian Xu et al.
APPLIED OPTICS (2019)
Modal Strain Energy-based Structural Damage Identification: A Review and Comparative Study
Shuqing Wang et al.
STRUCTURAL ENGINEERING INTERNATIONAL (2019)
Deep learning enhancement of infrared face images using generative adversarial networks
Axel-Christian Guei et al.
APPLIED OPTICS (2018)
Hurst based vibro-acoustic feature extraction of bearing using EMD and VMD
Satish Mohanty et al.
MEASUREMENT (2018)
A Novel Fault Diagnosis Method for Rotating Machinery Based on a Convolutional Neural Network
Sheng Guo et al.
SENSORS (2018)
Convolutional neural networks for automated damage recognition and damage type identification
Ceena Modarres et al.
STRUCTURAL CONTROL & HEALTH MONITORING (2018)
Structural Damage Detection with Automatic Feature-Extraction through Deep Learning
Yi-zhou Lin et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2017)
ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky et al.
COMMUNICATIONS OF THE ACM (2017)
Adjustable hybrid resampling approach to computationally efficient probabilistic inference of structural damage based on vibration measurements
Wei Zheng et al.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING (2016)
Variational Mode Decomposition
Konstantin Dragomiretskiy et al.
IEEE TRANSACTIONS ON SIGNAL PROCESSING (2014)
Bayesian analysis of the Phase II IASC-ASCE structural health monitoring experimental benchmark data
J Ching et al.
JOURNAL OF ENGINEERING MECHANICS-ASCE (2004)